Earticle

초록

영어

Given the performance of original affinity propagation algorithm is greatly affected by preference (P), stability threshold-based affinity propagation clustering algorithm (STAP) is proposed in this paper, including stability threshold to obtain the state of convergence when getting real class number and capture the corresponding P, and it take S-type function as damping factor to accelerate the convergence speed of STAP clustering algorithm. Besides it is successfully applied in the financial evaluation of public companies. The simulation experimental results show that, comparing the traditional affinity propagation clustering algorithm, STAP clustering algorithm can obtain high precision and fast convergence rate to improve clustering performance.

목차

Abstract
 1. Introduction
 2. Affinity Propagation Clustering Algorithm
 3. Stability Threshold-Based Affinity Propagation ClusteringAlgorithm
  3.1 The Optimization of Preferences
  3.2. The Accelerating Technology with S-type Function
 4. Experimental Results and Analysis
 5. Experimental Results and Analysis
 6. Conclusions
 Acknowledgements
 References

키워드

저자

• Limin Wang [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]
• Yizhang Wang [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]
• Xuming Han [ School of Computer Science and Engineering Changchun University of Technology, Jilin, 130117, China ] Corresponding author
• Qiang Ji [ School of Management science and information engineering, Jilin University of finance and economics, Jilin, 130117, China, Jilin Province Key Laboratory of Internet Fintech, Jilin University of Finance and Economics, Changchun 130117, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Database Theory and Application

• 간기

  격월간

• pISSN

  2005-4270

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605